deepseek-harness/packages/bundle/base/cordis.patch.yml

# The dsh-base bundle patch: the shared core of every dsh profile, applied as
# ONE insert over the empty profile root. Later bundle patches and the user's
# profile cordis.patch.yml address these rows by id, with the last write
# winning per row.
#
# A patch replaces the targeted row's whole `config` rather than merging into
# it, so a row whose value differs by mode does NOT live here: it belongs to
# each mode bundle, keeping any single row down to one bundle layer plus the
# user's. Mode-specific rows appear below only with shared plugin identity and
# neutral defaults; each mode bundle restates its complete configuration.
#
# Row order carries no load semantics (activation is service-availability
# driven); the grouping is for readers.

- insert:
    - id: timer
      name: '@cordisjs/plugin-timer'

    - id: hmr
      name: '@cordisjs/plugin-hmr'
      config:
        root: ['.']

    # The profile's cordis.patch.yml replaces this row's config to select exact GitHub
    # repository Plugin generations. The app registers the DSH-owned runtime even
    # when the list is empty so a later personal-config edit can load
    # transactionally; one-shot headless runs consume the startup value only.
    - id: repository-plugins
      name: '@deepseek-ai/dsh-repository-plugin'

    - id: llm
      name: '@deepseek-ai/dsh-llm'

    - id: session
      name: '@deepseek-ai/dsh-session'

    - id: session-title
      name: '@deepseek-ai/dsh-session-title'
      config:
        fallbackMaxWords: 5
        fallbackMaxBytes: 40
        maxTitleBytes: 80

    - id: session-title-llm
      name: '@deepseek-ai/dsh-session-title-first-message-llm'
      config:
        targetWords: 5
        targetCjkCharacters: 10
        maxInputBytes: 4096
        maxOutputTokens: 64
        timeoutMs: 60000

    - id: user-interaction
      name: '@deepseek-ai/dsh-user-interaction'

    - id: agent
      name: '@deepseek-ai/dsh-agent'

    - id: tasks
      name: '@deepseek-ai/dsh-tasks-local'

    - id: llm-retry
      name: '@deepseek-ai/dsh-llm-retry'

    # User-settings document (`$DSH_HOME/settings.yaml`, hot-reloaded): a
    # `llm-deepseek:` or `llm-pi-ai:` section there overrides the adapter entries
    # below without a restart, and is what the web Models page writes.
    - id: settings
      name: '@deepseek-ai/dsh-settings-local'

    # Credential store: the live process environment over `$DSH_HOME/.env`
    # (owner-only file, hot-reloaded). Adapters resolve their key references
    # through it at each request, so no key is inlined in this file. The web
    # Models page's key inputs write it through `credentials.set`; nothing hoists
    # the document into the process environment, which would make every stored key
    # read as an unrotatable ambient override.
    - id: credentials
      name: '@deepseek-ai/dsh-credentials-local'

    # The pi-ai multi-provider twin, mounted dormant: zero routes (and no extra
    # models in the picker) until a `llm-pi-ai:` settings section supplies provider
    # profiles — then those routes register live, keys resolving per request
    # through their apiKeyEnv references, and drop again when the section empties.
    # Supplying those profiles is exactly what the web Models page does. Which
    # adapters exist is composition; which providers run is the user's settings
    # document.
    - id: llm-pi-ai
      name: '@deepseek-ai/dsh-llm-pi-ai'

    - id: session-persistence-jsonl
      name: '@deepseek-ai/dsh-session-persistence-jsonl'
      config:
        root: !!js dshHomePath('sessions')

    # Raw configs can supply a process-local path or disable this shared session
    # capability. The neutral default is process-local and opens only when used.
    - id: session-query-sqlite
      name: '@deepseek-ai/dsh-session-query-sqlite'
      config:
        path: ':memory:'
        openAt: first-search

    # Shared projection registry: subagent catalog identity (mode/label) folds
    # through its registered units, so the `list_agents` surface below fails
    # loud without it; web layers reuse this same mount for list rows.
    - id: session-projection
      name: '@deepseek-ai/dsh-session-projection'

    # Session telemetry, on for every dsh mode: mirrors every session-log
    # event (assistant/chunk projected to first-of-step) plus ops markers onto
    # OTLP/HTTP log records, streaming on the batch processor's cadence
    # (10s/batch here) — not at exit; a crash loses at most the last unexported
    # interval. No telemetry/record redaction rule is mounted yet, so exports
    # are the raw captured copy; the deployment stance, env seams, and
    # follow-ups are pinned in the web-telemetry-default-mount Agent Note.
    # DSH_TELEMETRY_OTLP_URL overrides the production endpoint, and a non-empty
    # DSH_TELEMETRY_DISABLED — any value, including '0'/'false' — opts the
    # process out (the launchers patch the row disabled; config cannot disable
    # a row). Exports carry the harness home's anonymous user id ($DSH_HOME/.userid,
    # random UUID; delete the file to reset the identity) as the Resource's
    # user.id. The exporter/processor values normally bound the shutdown drain
    # to ~1s against an unreachable collector: exporter.timeoutMillis is both
    # the per-attempt socket timeout and the retry deadline (1s effectively
    # disables the SDK's 5-try backoff), while maxExportBatchSize == maxQueueSize
    # (both explicit) makes the drain a single batch. The SDK awaits
    # exporter.forceFlush() outside exportTimeoutMillis, so the backend's 3s
    # shutdownTimeoutMillis is the load-bearing outer bound when a transport
    # promise never settles. Every CLI exit path drains it by disposing the root
    # on SIGINT/SIGTERM.
    - id: telemetry-otel
      name: '@deepseek-ai/dsh-session-telemetry-otel'
      config:
        shutdownTimeoutMillis: 3000
        exporter:
          url: !!js process.env.DSH_TELEMETRY_OTLP_URL ?? 'https://harness-telemetry.deepseeksvc.com/v1/logs'
          compression: gzip
          timeoutMillis: 1000
        processor:
          scheduledDelayMillis: 10000
          maxQueueSize: 2048
          maxExportBatchSize: 2048
          exportTimeoutMillis: 1500

    - id: subprocess
      name: '@deepseek-ai/dsh-subprocess-local'

    # Every shipped CLI mode starts with the same file-effect boundary.
    # The environment remains an explicit deployment override; otherwise fresh
    # sessions pin workspace-write + ask through the permission service below.
    - id: sandbox
      name: '@deepseek-ai/dsh-sandbox-local'

    - id: sandbox-policy
      name: '@deepseek-ai/dsh-sandbox-policy'
      config:
        mode: !!js process.env.DSH_PERMISSION_MODE ?? 'workspace-write'
        workspaceRoot: !!js process.cwd()

    - id: bash-sandbox
      name: '@deepseek-ai/dsh-bash-sandbox'
      config:
        timeoutMs: 60000

    - id: approval
      name: '@deepseek-ai/dsh-user-approval'
      config:
        policy: !!js "(process.env.DSH_PERMISSION_MODE ?? 'workspace-write') === 'danger-full-access' ? 'never' : 'ask'"

    - id: permission
      name: '@deepseek-ai/dsh-permission'
      config:
        presets:
          read-only:
            sandbox: read-only
            approval: ask
          workspace-write:
            sandbox: workspace-write
            approval: ask
          danger-full-access:
            sandbox: danger-full-access
            approval: never

    - id: bash-env
      name: '@deepseek-ai/dsh-bash-env'

    - id: tool-bash
      name: '@deepseek-ai/dsh-tool-bash'

    - id: tool-tasks
      name: '@deepseek-ai/dsh-tool-tasks'

    - id: fs-policy
      name: '@deepseek-ai/dsh-fs-policy'

    - id: tool-fs
      name: '@deepseek-ai/dsh-tool-fs'

    - id: tool-fs-search
      name: '@deepseek-ai/dsh-tool-fs-search'
      config:
        sampleOverCapGlobResults: false

    - id: workspace-context
      name: '@deepseek-ai/dsh-workspace-context'
      config:
        maxBytes: 65536

    - id: skill
      name: '@deepseek-ai/dsh-skill'

    - id: skill-local
      name: '@deepseek-ai/dsh-skill-local'

    - id: tool-skill
      name: '@deepseek-ai/dsh-tool-skill'

    - id: commands
      name: '@deepseek-ai/dsh-commands'

    - id: goal
      name: '@deepseek-ai/dsh-goal'

    - id: goal-session
      name: '@deepseek-ai/dsh-goal-session'

    - id: command-goal
      name: '@deepseek-ai/dsh-command-goal'

    - id: plan-mode
      name: '@deepseek-ai/dsh-plan-mode'
      config:
        section: |
              You are in plan mode. Stay in plan mode until exit_plan_mode succeeds or the user switches the session mode. Imperative language to implement changes means plan the implementation, not execute it. A user's conversational agreement — including an answer confirming something you asked — approves nothing and does not end plan mode; fold the confirmed decision into the plan and submit it through exit_plan_mode.

              Explore first. Use non-mutating reads, searches, static analysis, and checks to ground the plan in the actual repository. Do not edit or write files, change configuration, run formatters or code generation that rewrites tracked files, commit, or otherwise carry out the plan. Prefer existing functions and patterns over new machinery.

              The tool catalog stays the same across modes for request-cache stability. These plan-mode rules override any later tool description or guidance that suggests using mutation tools; those tools remain listed only to keep the request shape stable. Do not use todo_write to track this planning phase: it tracks implementation after an approved plan, while the plan itself belongs in exit_plan_mode.

              Resolve discoverable facts by inspection. Use ask_user_question only for user-owned choices or material ambiguity that inspection cannot answer. Do not ask the user where code lives or how current behavior works when you can find out.

              Make the plan decision-complete: state the goal and success criteria; group implementation changes by subsystem; identify public API, schema, and data-flow changes; cover edge cases, failure modes, tests, acceptance criteria, and explicit assumptions. Keep it concise enough to review but detailed enough that another engineer can implement it without making design decisions.

              When ready, call exit_plan_mode with the complete plan markdown, starting with a # title. Make exit_plan_mode the only and final tool call in that assistant response: it presents the plan for approval, and implementation begins only in a later step after approval. Do not paste the final plan as a plain reply or ask "should I proceed?" through prose or ask_user_question. If review rejects it, incorporate the feedback and present again. If the review channel is unavailable or aborted, stay in plan mode and ask the user to switch modes manually; do not proceed with implementation.

    - id: token-meter
      name: '@deepseek-ai/dsh-token-meter'

    - id: compact-basic
      name: '@deepseek-ai/dsh-compact-basic'

    # Human `/compact`: one useful reduction below the automatic threshold. Backend
    # independent, so it follows whichever compaction service this leaf mounts.
    - id: command-compact
      name: '@deepseek-ai/dsh-command-compact'

    - id: subagent
      name: '@deepseek-ai/dsh-subagent'

    - id: subagent-spawn
      name: '@deepseek-ai/dsh-subagent-spawn'
      config:
        providerName: spawn

    - id: subagent-fork
      name: '@deepseek-ai/dsh-subagent-fork'
      config:
        providerName: fork

    # Continuable background children are selected per delegation tool. The
    # separately loaded follow-up tool registers the one global `send_message`.
    - id: tool-subagent-control
      name: '@deepseek-ai/dsh-tool-subagent-control'

    - id: tool-subagent-list-agents
      name: '@deepseek-ai/dsh-tool-subagent-control/list-agents'

    - id: tool-subagent
      name: '@deepseek-ai/dsh-tool-subagent'
      config:
        provider: spawn
        toolName: subagent
        backgroundMode: continuable

    - id: tool-subagent-fork
      name: '@deepseek-ai/dsh-tool-subagent'
      config:
        provider: fork
        toolName: subagent_fork
        backgroundMode: continuable

    # Optional direct-child return channel; absent from roots and one-shot agents.
    - id: tool-subagent-report
      name: '@deepseek-ai/dsh-tool-subagent-report'

    - id: workflow-workerthread
      name: '@deepseek-ai/dsh-workflow-workerthread'
      config:
        provider: spawn

    - id: tool-workflow
      name: '@deepseek-ai/dsh-tool-workflow'

    - id: timeout-policy
      name: '@deepseek-ai/dsh-timeout-policy'

    - id: spill-local
      name: '@deepseek-ai/dsh-spill-local'

    - id: spill-policy
      name: '@deepseek-ai/dsh-spill-policy'
      config:
        maxInlineBytes: 50000

    # Durability checkpoints before each model request and top-level dispatch.
    - id: session-checkpoint-policy
      name: '@deepseek-ai/dsh-session-checkpoint-policy'

    # Compacts oversized tool results before the broader conversation compactor
    # runs, preserving the model-visible result within the configured budget.
    - id: tool-result-prune
      name: '@deepseek-ai/dsh-compact-tool-result-prune'
      config:
        thresholdChars: 8192
        headChars: 4096
        tailChars: 1024

    - id: tool-todo
      name: '@deepseek-ai/dsh-tool-todo'
      config:
        allowParallelInProgress: true

    # Persisted same-session goals reach the model and the slash menu here; the
    # domain, driver, and `/goal` command are above.
    - id: tool-goal
      name: '@deepseek-ai/dsh-tool-goal'

    # Fresh-agent Ralph iteration over a build-time-fixed script.
    - id: tool-ralph
      name: '@deepseek-ai/dsh-tool-ralph'
      config:
        subagentProvider: spawn
        maxRounds: 64

    - id: tool-str-replace-editor
      name: '@deepseek-ai/dsh-tool-str-replace-editor'
      config:
        maxOutputChars: 16000

    # Consecutive-repeat reminders on the tool chain.
    - id: repeat-tool-guard
      name: '@deepseek-ai/dsh-repeat-tool-guard'
      config:
        thresholds: [3, 5, 8]
        argumentsPreviewChars: 500

    # Every mode enables the stable web_search model surface. DeepSeek search
    # resolves the same DEEPSEEK_API_KEY credential the Models page manages for
    # chat, at each search; its Messages endpoint is separate from the
    # chat-completions endpoint, so it takes its own base-URL override. Fetch stays
    # disabled and no fetch provider is mounted: that provider defers SSRF
    # protection and the model would choose the request target. Search is a full
    # auxiliary model request with server-side retrieval, so this shipped DeepSeek
    # route gets 60s while the provider-neutral tool default remains 30s.
    - id: web
      name: '@deepseek-ai/dsh-web'
      config:
        searchProvider: deepseek-official

    - id: web-search-deepseek
      name: '@deepseek-ai/dsh-web-search-deepseek'
      config:
        apiKeyEnv: DEEPSEEK_API_KEY
        baseURL: !!js process.env.DEEPSEEK_SEARCH_BASE_URL

    - id: tool-web
      name: '@deepseek-ai/dsh-tool-web'
      config:
        fetch: false
        searchTimeoutMs: 60000

    # ── rows every mode mounts, whose values each overlay may state ──────────────

    # The tool registry. Presentation mode is a deployment choice; omitting it here
    # keeps the schema default (native).
    - id: tools
      name: '@deepseek-ai/dsh-tools'

    # The deployment persona is a deployment choice; plan-mode and tool plugins own
    # their own prompt sections.
    - id: system-prompt
      name: '@deepseek-ai/dsh-system-prompt'
      config:
        persona: ''

    # Agents created at startup. The base stays empty; raw overlays may create
    # agents, while Web creates sessions on client request.
    - id: agent-loop
      name: '@deepseek-ai/dsh-agent-loop'
      config:
        agents: []

    # The sandboxed filesystem provider. `cwd` defaults to `process.cwd()`; an
    # overlay can pin another workspace.
    - id: fs-sandbox
      name: '@deepseek-ai/dsh-fs-sandbox'

    # The native DeepSeek adapter. No key or endpoint is inlined: both resolve per
    # request from the `llm-deepseek:` settings section over this entry, with the
    # key coming from the credential store below. Thinking defaults are a deployment
    # choice.
    - id: llm-deepseek
      name: '@deepseek-ai/dsh-llm-deepseek'